Sentiment analysis of Algerian dialect

Abstract

As technology continues to advance, sentiment analysis has become one of the prominent research areas in natural language processing and machine learning. Sentiment analysis focuses on the computational study of emotions and sentiments expressed in written texts. Social data has become one of the most important sources of data in this field. While most current research focuses on sentiment analysis of English texts, there is limited interest in sentiment analysis of Arabic, particularly Algerian dialect. In this work, we propose a sentiment analysis model for Algerian dialect classification that includes two main steps: the first step is preprocessing, where raw textual data is cleaned and emojis are translated into text. The second step is the classification, where three classification algorithms are applied to the processed text.